Artificial intelligence technology has proven to be a bliss for many industries and has helped to solve fundamental issues related to the challenges faced. In the health field, too, this has been beneficial, especially with regard to diagnosis. AI will be used more and more in healthcare, according to a recent study published in the Future Healthcare Journal, especially for tasks such as diagnosis and treatment recommendations, patient engagement and adherence , and administrative operations of health personnel.
There are intriguing opportunities for AI in the medical profession, how it could improve the treatment process, and some of the most successful AI applications for medical purposes. The use of deep learning in medical diagnostics to detect cancer is an important development of AI in medicine. According to a recent study published in the Journal of the National Cancer Institute, the AI system can detect breast cancer with the same accuracy as a typical breast radiologist.
With the ability of AI networks to train constantly, it is highly likely that their performance will improve significantly in the near future. Another interesting deployment is the use of AI and the medical Internet of Things in consumer healthcare applications. These systems combine medical IoT devices to collect health data and AI-based applications to assess the data and make recommendations based on the patient’s current lifestyle.
The patient-centered approach of medical software developers has sparked demand for home health solutions. Artificial intelligence is widely used for the management of high risk disorders. Telehealth tools are being put in place for patients at home to treat and prevent high-risk situations while reducing hospitalizations. These telehealth tools make it possible to take, document and process different metrics much like a larger AI machine. This equipment can alert physicians when a patient is at high risk. This allows for early detection, faster diagnoses, and a subsequent treatment plan that reduces time and financial burden.
The best part about using AI in healthcare is that it can be applied to a variety of fields, from collecting and processing crucial patient data to creating surgical robots. Let’s take a closer look at the top five medical applications of artificial intelligence:
1. Classification of diseases
The ability of deep learning technology to examine images and find patterns opens up the possibility of developing algorithms to help physicians diagnose disease faster and more accurately. These algorithms can learn over time, increasing their accuracy to guess the correct diagnosis.
Medical diagnostic tests such as MRIs, X-rays and CT scans, AI-based software can be taught to correctly recognize indications of a certain disease. Similar technologies that process images of skin lesions have already used AI for cancer diagnosis.
2. Increase the efficiency of decision-making
Diagnostic and therapeutic procedures have always been difficult. This is because clinicians need to look at the patient’s symptoms, potential research errors, all known treatment methods, potential side effects, diseases with very similar symptoms, and many other factors at the same time.
Modern AI-powered solutions are already helping physicians overcome research challenges, process large amounts of health data quickly, and ensure a complete understanding of a patient’s health.
3. Treatment options based on artificial intelligence
Even after a disease has been identified and categorized, the treatment process can lead to further complications. A treatment plan doesn’t just include prescription drugs and exercise. Modern AI algorithms are now helping clinicians to implement a comprehensive disease management strategy.
Artificial intelligence in medical diagnostics is already a reality, despite the fact that both the healthcare industry and AI are still evolving and have many complex challenges to overcome.
Patients can use Google Health to track their fitness progress and get information about their health, nearby hospitals, and medication recalls.
A concrete example of the benefits of AI in diagnostics in our country was in Indore when the Apple Watch’s ECG function saved the life of a 61-year-old man by detecting irregular heartbeats.
Clearly, AI is already changing the medical industry by helping clinics better organize their workflow, making diagnostics and decision-making easier for physicians, and providing important lifestyle adjustments for patients.
Industry experts predict that not only will existing AI-based medical diagnostic solutions be improved, but new ways to merge AI with medicine will also emerge. For example, AI should speed up the drug development process.
Prabhat Pankaj, Technical Director, Redcliffe Life Diagnostics
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